1. Field of the Invention
The present invention relates generally to character recognition on a bit-mapped binary image or other binary or raster images and more particularly to recognition of non-text and/or text objects on the document image.
The abovementioned methods are also used in forms recognition. Said forms combine portions of typographical and hand-written text along with a set of special reference points meant for orientating on the document or form. Some examples of forms are questionnaires, bank invoices of fixed or non-fixed field layout.
Said methods can be also used for the recognition of objects of any pre-defined kind on a bit-mapped image.
2. Prior Art
Segmentation and parsing methods are known in the art.
Today there is a number of known methods of image recognition on a bit-mapped image by performing a comparison between an obtained image in the form of initial image units aggregate (commonly pixels) and a model image of the whole object or a set of possible object's embodiments stored in a special reference means usually termed classifier.
A known group of methods of text recognition comprises parsing the document into parts presumably containing images of letters with the further comparison of said images with those stored in one or more special feature and/or raster classifiers.
The said method is disclosed, for example, in U.S. Pat. No. 5,680,479 (Oct. 21, 1997, Wang, et al.).
A similar method is disclosed in U.S. Pat. No. 5,684,891 (Nov. 4, 1997, Tanaka, et al.). The document describes a method of image parsing that enables to pick out a separate character images, which in the author's opinion makes the process more reliable. The character image as an aggregate of pixels is then compared with the model from a classifier.
A shortcoming of the method is that it uses full-sized images and full-sized models for comparison, which inevitably reduces the productivity of the process.
Therefore, the target of the present invention is to increase the reliability of objects recognition, to increase the noise immunity.